Children's Health Survey

Inspiration

How can you actually know if your child is going through a tough time and needs help? This project aims to give parents a tool by which to understand their children and gauge whether they need more help.

What it does

The algorithm we created using machine learning can analyze the answers to a simple survey and determine whether a child may need more medical care, mental health services, or educational support than other children in their peer group.

How we built it

First we acquired data from a survey of parents about their children, throughout the United States, from the CDC. With that, we were able to use Microsoft Azure Machine Learning Studio to create a model based on the data. More specifically, we had to clean up the data by getting rid of extraneous information and changing certain values into something the software could work with. From there the machine used the data to learn correlations between answers to certain survey questions that we were interested in, and this could be incorporated into a survey for parents.

Challenges we ran into

It was difficult at first to find the right data to work with and to find questions that could be answered by data. It is important that the information and the question work together to create a product that is both useful and reasonable.

Accomplishments that we're proud of

We are proud of our success in using Microsoft's Azure Machine Learning Studio to analyze CDC data.

What we learned

We learned how to use Microsoft Azure Machine Learning Studio and how important it is to obtain the right data for the right situations, as well as getting rid of data that is unnecessary.

What's next for Children's Health Survey

Built With

• html
• microsoft-azure-machine-learning-studio